Dr. Byon’s research interests include reliability evaluation, fault diagnosis/condition monitoring, predictive modeling and data analytics, and operations and maintenance decision-making for stochastic systems. Her recent research focuses on uncertainty quantification of stochastic systems using stochastic simulations, reliability analysis and improvement of large-scale, interconnected systems with applications to renewable power power systems and manufacturing processes. She is a member of IIE, INFORMS, and IEEE.
Byon, E., Choe, Y., Yampikulsakul N., Adaptive modeling and prediction in time-variant processes with application to wind power systems, to appear in IEEE Transactions on Automations Science and Engineering.
Choe, Y., Byon, E., and Chen, N., 2015, Importance sampling for the reliability evaluation with stochastic simulation models, Technometrics, Vol. 57, No. 3, pp. 351-361.
Ko. Y and Byon, E., Reliability analysis of large-scale systems with identical units, 2015, IEEE Transactions on Reliability, Vol. 64, No. 1, pp. 420-434.
Yampikulsakul N., Byon, E., Huang S., Sheng S. and You M.*, 2014, Condition monitoring of wind turbine system with nonparametric regression-based analysis, IEEE Transactions on Energy Conversion, Vol. 29, No. 2, pp. 288-299.
Byon, E., 2013, Wind turbine operations and maintenance: A tractable approximation of dynamic decision-making, IIE Transactions, Vol. 45, No. 11, pp. 1188-1201
Lee, G., Byon, E., Ntaimo, L., and Ding. Y, 2013, Bayesian spline method for assessing extreme loads on wind turbines, Annals of Applied Statistics, Vol. 7, No. 4, pp. 2034–2061
Byon, E., Shrivastava, A. K., and Ding, Y., 2010, A classification procedure for highly imbalanced class sizes, IIE Transactions, Vol. 42, No. 4, pp. 288-303